CST 241 - Deep Learning

The course provides an understanding of the application of Deep Learning techniques, including Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), for classifying unstructured data such as images and text. Students will learn to design, implement, and evaluate pipelines for supervised classification of structured data using various Machine Learning techniques, such as Logistic Regression. Additionally, important considerations for applying Machine Learning in practice will be discussed, ensuring students are equipped to handle real-world challenges.
Prerequisite(s): ENG 097, MAT 144 or MAT 155, CST 206, and CST 161 or permission from Dean.
2 lecture hours and 2 laboratory hours per week
3 credit hours